Introduction to the team software process
Introduction to the team software process
A Discipline for Software Engineering
A Discipline for Software Engineering
A Critical Analysis of PSP Data Quality: Results from aCase Study
Empirical Software Engineering
Empirically Guided Software Effort Guesstimation
IEEE Software
Teaching the PSP: Challenges and Lessons Learned
IEEE Software
Application Challenges: System Health Management for Complex Systems
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Measuring Team Activities in a Process-Oriented Software Engineering Course
CSEET '98 Proceedings of the 11th Conference on Software Engineering Education and Training
Aspect-Oriented Implementation of Software Health Indicators
APSEC '01 Proceedings of the Eighth Asia-Pacific on Software Engineering Conference
Proceedings of the 35th SIGCSE technical symposium on Computer science education
ISESE '04 Proceedings of the 2004 International Symposium on Empirical Software Engineering
ClockIt: collecting quantitative data on how beginning software developers really work
Proceedings of the 13th annual conference on Innovation and technology in computer science education
Retina: helping students and instructors based on observed programming activities
Proceedings of the 40th ACM technical symposium on Computer science education
Hi-index | 0.00 |
For empirical software engineering to reach its fullest potential, we must develop effective, experiential approaches to learning about it in a classroom setting. In this paper, we report on a case study involving a new approach to classroom-based empirical software engineering called the “Software ICU”. In this approach, students learn about nine empirical project “vital signs” and use the Hackys-tat Framework to put their projects into a virtual “intensive care unit” where these vital signs can be assessed and monitored. We used both questionnaire and log data to gain insight into the strengths and weaknesses of this approach. Our evaluation provides both quantitative and qualitative evidence concerning the overhead of the system; the relative utility of different vital signs; the frequency of use; and the perceived appropriateness outside of the classroom setting. In addition to benefits, we found evidence of measurement dysfunction induced directly by the presence of the Software ICU. We compare these results to case studies we performed in 2003 and 2006 using the Hackystat Framework but not the Software ICU. We use these findings to orient future research on empirical software engineering both inside and outside of the classroom.